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P09 / scientific study / published

CNT Conductivity, Percolation and Network Models

Resistor-network and finite-element models predicted electrical percolation and conductivity against measured nanocomposite data.

2020-2024Northumbria University, United Kingdom
COMPUTATIONAL VALIDATION LOOPCNT Conductivity, Percolation and Network Models
01PHYSICAL QUESTIONrequirements / mechanisms / scales
02MODELRVE / RNM / DEM / FEM / FEA
03SOLVECST / HFSS / COMSOL / ANSYS / Abaqus
04VALIDATERF / mechanical / electrical experiments
05REFINEPython / MATLAB / sensitivity analysis
06ENGINEERprototype / instrument / deployment

Models are tested against experiments and returned to engineering decisions.

01

Problem or Industrial Need

Conductive nanocomposite design depends on predicting when random CNT networks establish electron transport and how tunnelling distance affects conductivity.

02

Engineering or Scientific Solution

Parallel three-dimensional resistor-network and finite-element models validated against electrical measurements.

03

Sebastian's Technical Contribution

Developed numerical models and software, performed formal analysis and compared predicted conductivity with experiments.

04

Methods and Tools Used

  • MATLAB resistor-network modelling
  • DIGIMAT finite-element analysis
  • Tunnelling-distance and percolation-probability analysis
  • Electrical measurement validation
05

Prototype, Simulation and Experimental Evidence

simulation

Two numerical methods

Resistor-network and FEM approaches independently evaluated electrical transport.

experiment

Conductivity measurements

Measured nanocomposite behaviour provided the validation reference.

publication

Materials Today: Proceedings 2022

Peer-reviewed experimental and numerical investigation.

06

Measurable Result or Published Finding

around 2 wt%

reported percolation threshold

Both modelling approaches captured the experimentally observed conductivity transition.

07

Diagrams and Publications

COMPUTATIONAL VALIDATION LOOPCNT Conductivity, Percolation and Network Models
01PHYSICAL QUESTIONrequirements / mechanisms / scales
02MODELRVE / RNM / DEM / FEM / FEA
03SOLVECST / HFSS / COMSOL / ANSYS / Abaqus
04VALIDATERF / mechanical / electrical experiments
05REFINEPython / MATLAB / sensitivity analysis
06ENGINEERprototype / instrument / deployment

Models are tested against experiments and returned to engineering decisions.

08

Role, Team Attribution, Institution and Project Context

Lead author and Doctoral Researcher; software, investigation, modelling and formal analysis.

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Computational Multiphysics and Experimental Validation

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No single model explains how nanoscale morphology, transport, mechanics and electromagnetic response combine in a sensing material.
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A computational stack that moves between RVE, resistor-network, diffusion, mechanical and electromagnetic models and closes the loop with experiments.
Evidence / result
Physics-to-instrument reasoning
FEM/FEARVEresistor networkdiffusion
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